Real-world applications of quantum-enhanced machine learning solutions Koduri Sreelakshmi, Vishal V. Rathi, K. Shanthi, Shikalgar Niyaj Dilavar, S. Logeswaran, B. Subhi Exploring the Fusion of Quantum Computing and Machine Learning, 2025 QML is the quantum machine learning, a new approach to explore the potential of quantum computation allowing us to discover solutions that otherwise would be hard for a classical computer to find. A variety of applied QML areas will be highlighted in the following chapter such as optimization problems NLP, drug discovery. Some foundations of quantum- superposition and entanglement- are designed to provide more efficient approach- towards higher fidelity in all data driven pipelines. This chapter gives some practical use cases for integration of quantum algorithms into pipelines of machine learning as well as some main challenges (i.e., regarding noise, scalability and algorithm selection) concerning it. Hybrid quantum-classical schemes are thought as the key for progress towards practicality on currently available noisy intermediate-scale quantum hardware. In this chapter, we will address QML viewpoints of the operational strategy and future, including potential QML disruptive effects and the future adoption insights of QML.
Energy harvesting and management in body-focused wireless sensor networks Jamuna K. M., Shanmugasundaram Senathipathi, Santosh Dubey, S. Kolangiammal, Shikalgar Niyaj Dilavar, Sampath Boopathi Battery Free Sensor Networks for Sustainable Next Generation Iot Connectivity, 2025 Body-focused wireless sensor networks have surfaced as the leading-edge technology in healthcare, wearable electronics, and human-computer interaction – a critical dimension for continuous health monitoring and remote diagnostics. BF-WSNs face challenges in advancing due to nodes' lack of battery life, which is crucial for long-term, uninterrupted operation. This chapter explores higher-order energy harvesting and management strategies within BF-WSNs with an emphasis on sustained sources like thermal, kinetic, and photovoltaic energy. The chapter discusses low-power circuit design, duty cycling, data transmission optimization, and energy-aware protocols for BF-WSNs. It explores efficient energy management frameworks to extend operational lifetimes and reduce battery dependency and highlights energy harvesting's potential in developing self-sufficient wireless sensor networks.
CFD-BASED NUMERICAL INVESTIGATION OF CROSSFLOW FAN PERFORMANCE Niyaj Shikalgar, Avinash Deshmukh, Vidya Zinjurde International Journal of Fluid Mechanics Research, 2025 A crossflow fan (CFF) is a turbomachine that works differently than axial or centrifugal fans. Using computational methods, the study shows the complicated flow phenomena of a CFF. The effect of the geometric impeller and casing characteristics, such as blade angles, number of blades, and radius ratio on the flow field of a CFF, is investigated using computational methods. Flow metrics, such as total pressure, static pressure, and velocity components, suggest that flow inside and around the impeller can be considered two-dimensional. When the number of blades is raised from 16 to 21, the pressure area increases from 2.5 to 5.6 pa, while the total torque increases from 6.7 to 8.1 N-mm. We get a total pressure of 11.6 pa and a torque of 6.5 N-mm if the outer diameter of a fan is 62 mm and all other parameters are kept constant. There is more flow leakage via the tongue clearance area at low flow coefficients. As the flow coefficient declined, the vortex drifted closer to the center, and at a circumferential point, the total pressure created by the impellers was determined to be the highest. In the casing, there is secondary flow that is perpendicular to the actual flow.
Performance assessment of a refrigerator with a hot-wall condenser under O-to-D grooved geometrical conditions Niyaj SHIKALGAR Materials Research Proceedings, 2025 The heat transfer abilities of hot-wall condensers applied to domestic refrigerators are addressed in the present research. This investigation addresses the effect of a variation of the contact area between the pipe and back plate of a condenser, which was not examined previously as a design parameter for the heat transfer analysis of a condenser. The design parameters were incorporated into the manufacturing of the hot wall condenser samples for testing. Furthermore, to compare the results of the experimental discoveries regarding thermal effects, a simulation model was developed. Temperature profiles and heat transfer coefficients were measured along the condensers. AS/NZS 4474-1997 is used to examine the household refrigerator's performance. The compressor's energy consumption, pull-down time, and COP at 28°C ambient temperature using traditional methods are computed by employing a condenser under various operational circumstances. The findings provided significant insight into how different design elements impacted the condenser's heat transfer rate. More precisely, increasing the surface area of the condenser pipe enhanced the heat transfer rate by an average of 9.31%. It was demonstrated that keeping the pipe pitch at 40 mm had a major influence on the heat transfer rates. More specifically, switching from an O-to-D pipe layout can increase the overall heat transfer rate by as much as 4%, making it a novel output.
Autonomous Vehicle Suspension Systems: IOT Data Analytics with Deep Learning Models Shikalgar Niyaj Dilavar, Lakshmi Kanthan Bharathi, R Narmatha Banu, Jagadeeshwaran A, M. Jeyamumgan, M. Arul Selvan 2025 2nd International Conference on Computing and Data Science Iccds 2025, 2025 The suspension management unit plays a critical role in ensuring vehicle stability and delivering a smooth driving experience by accurately predicting the road profile and the internal state variables of the suspension system. However, conventional observer-based methods face significant challenges, as the four key state variables-such as vertical acceleration, damper force, and wheel displacement-cannot be directly measured using commercial sensors. Traditional model-based techniques suffer from limitations due to model uncertainties, sensor noise, and high computational costs. To overcome these challenges, a data-driven deep learning framework is introduced. This model eliminates the need for explicit physical modeling, making the analysis faster, more adaptable, and computationally efficient. Validated on a simulated dataset, the proposed model demonstrates exceptional accuracy in estimating the desired variables with significantly lower processing times compared to traditional methods. Its performance is cross-validated against the physical characteristics of the suspension system, ensuring reliable and interpretable predictions. The model also showcases strong autoregressive capabilities, allowing it to forecast multiple future values of the state variables, enabling proactive suspension management. Comparative evaluations reveal that the deep learning model significantly outperforms existing baseline methods in terms of accuracy, processing speed, and robustness against varying road conditions. This advanced framework holds immense potential for enhancing ride comfort, vehicle stability, and overall performance, paving the way for smarter, real-time adaptive suspension systems, particularly in autonomous vehicles where precise suspension monitoring is essential for safe and reliable navigation.
REAL-TIME MONITORING AND OPTIMISATION SYSTEM FOR ADVANCED OXIDATION PROCESSES USING SMART SENSORS AND DATA ANALYTICS Oxidation Communications, 2025
Performance improvements of electric vehicles using edge computing and machine learning technologies Leena Raviprolu, Nagamani Molakatala, Rajesh V. Argiddi, Shikalgar Niyaj Dilavar, P. Srinivasan Solving Fundamental Challenges of Electric Vehicles, 2024 Edge computing and machine learning technologies have significantly improved electric vehicle (EV) performance, enhancing efficiency, reliability, and user experience by processing data closer to the vehicle, reducing latency, and conserving bandwidth. In this chapter, machine learning algorithms in EV edge infrastructure analysis data have been used for predictive analytics and optimization, predicting battery life, optimizing energy consumption, identifying potential failures, enhancing vehicle reliability, and reducing downtime. This chapter also illustrates battery management systems (BMS) using advanced machine learning techniques to monitor health, predict degradation, optimize charging cycles, and enable real-time decision-making for autonomous driving, enhancing safety and preventing overcharging. The practical challenges of integrating edge computing and ML in electric vehicles (EVs), highlighting data privacy, security, and infrastructure requirements, are also elaborated to improve performance.
Investigating Splashing Phenomena in Ice Trays Using Multiphase Volume of Fluid Modelling. ND Shikalgar, SR Kandharkar, SS Mundra, RA Patil, NA Rawabawale International Journal of Heat & Technology 43 (6) , 2025 2025
Metal Additive Manufacturing Materials: A State-of-the-Art Review. S Gadhave, S Kandharkar, N Shikalgar, S Nehe, V Mane, K Mahajan, ... Journal of Mines, Metals & Fuels 73 (10) , 2025 2025
Safety challenges in high-voltage electric vehicle collisions: risks and design strategies VK Agrawal, LN Patil, ND Shikalgar, YM Patil, V Javanjal, S Gadhave, ... Discover Electronics 2 (1), 53 , 2025 2025 Citations: 2
Investigating the Structural Integrity of Automotive B-pillars: The Effect of Ply Orientation on Composite Strength. K More, S Kandharkar, R Pawar, H Chavhan, P Honawadajkar, ... Journal of Mines, Metals & Fuels 73 (6) , 2025 2025
Performance assessment of a refrigerator with a hot-wall condenser under O-to-D grooved geometrical conditions N SHIKALGAR, A DESHMUKH, C CHOUDHARI Materials Research Proceedings 49 , 2025 2025
CFD-Based Numerical Investigation of Crossflow Fan Performance N Shikalgar, A Deshmukh, V Zinjurde International Journal of Fluid Mechanics Research 52 (4) , 2025 2025
Unmanned Ground Vehicle: Design and Development Approaches N Shikalgar, Y Patil, A Karale, M Patil, V Thadi, R Bankar 2024 International Conference on Intelligent Systems and Advanced … , 2024 2024
Optimization of 3D Plate Fin Heat Sinks Through Analytical Modelling N Shikalgar, P Chitale, SN Sapali Recent Advances in Thermal Sciences and Engineering: Select Proceedings of … , 2023 2023 Citations: 11
Experimental investigation of a capillary tube for 2 TR water chiller with R22 & R407C refrigerant AS Tupe, SN Sapali, N Shikalgar Materials Today: Proceedings 77, 818-822 , 2023 2023 Citations: 10
Design and development of an adequate ventilation system to preserve freshly harvested onions S Mandake, N Shikalgar, AM Deshmukh Materials Today: Proceedings 72, 943-950 , 2023 2023 Citations: 14
Design, development and experimentation of distillation unit for essential oil P Ilag, SN Sapali, N Shikalgar Materials Today: Proceedings 72, 664-671 , 2023 2023 Citations: 13
Mathematical Modeling of a Skin Condenser with Angular Contact for Domestic Refrigerator ND Shikalgar, SN Sapali, AB Shinde Applications of Computation in Mechanical Engineering: Select Proceedings of … , 2022 2022 Citations: 10
Design, Development, and Numerical Analysis of Mist Nozzle and Its Impact on Performance Parameters of an Evaporative Cooler AM Deshmukh, SN Sapali, AB Shinde, ND Shikalgar Applications of Computation in Mechanical Engineering: Select Proceedings of … , 2022 2022 Citations: 9
Predictive Analysis of Air-Cooled Condenser by Considering Fouling Using Machine Learning Algorithm ND Shikalgar, PR Gujari, SN Sapali, VD Chavan Recent Advances in Fluid Dynamics: Select Proceedings of ICAFFTS 2021, 225-234 , 2022 2022 Citations: 5
Exergy criteria of performance of waste heat recovery applied for marine auxiliary boiler JS Pal, SN Sapali, AT Ramakrishna, ND Shikalgar, A Shinde International Journal of Heat and Technology 40 (1), 297-303 , 2022 2022 Citations: 13
Experimental evaluation of the effect of leakage in scroll compressor ND Shıkalgar, SN Sapalı Journal of Thermal Engineering 9 (5), 1219-1227 , 2021 2021 Citations: 1
Assessment of Exergy Loss Rate in Marine Boiler to Analyze the Performance of Waste Heat Plant by the Exergy Method JS Pal, SN Sapali, TR Anil, ND Shikalgar Proceedings of the 26thNational and 4th International ISHMT-ASTFE Heat and … , 2021 2021
Analytical Modelling and Simulation of a Hot-Wall Condenser Applied to Domestic Refrigerator SN Sapali, ND Shikalgar Intelligent Electrical Systems:: A Step towards Smarter Earth, 65 , 2021 2021
Experimental Investigation of Solar Energy-Assisted DC Refrigerator ND Shikalgar, SN Sapali Intelligent Electrical Systems:: A Step towards Smarter Earth, 269 , 2021 2021
Energy and exergy analysis of a domestic refrigerator: approaching a sustainable refrigerator N Shikalgar Journal of Thermal Engineering 5 (5), 469-481 , 2019 2019 Citations: 45
MOST CITED SCHOLAR PUBLICATIONS
Energy and exergy analysis of a domestic refrigerator: approaching a sustainable refrigerator N Shikalgar Journal of Thermal Engineering 5 (5), 469-481 , 2019 2019 Citations: 45
Performance evaluation of a domestic refrigerator with a thermal storage arrangement using propane as a refrigerant DS Niyaj, SN Sapali Energy Procedia 109, 34-39 , 2017 2017 Citations: 31
Design and development of an adequate ventilation system to preserve freshly harvested onions S Mandake, N Shikalgar, AM Deshmukh Materials Today: Proceedings 72, 943-950 , 2023 2023 Citations: 14
Design, development and experimentation of distillation unit for essential oil P Ilag, SN Sapali, N Shikalgar Materials Today: Proceedings 72, 664-671 , 2023 2023 Citations: 13
Exergy criteria of performance of waste heat recovery applied for marine auxiliary boiler JS Pal, SN Sapali, AT Ramakrishna, ND Shikalgar, A Shinde International Journal of Heat and Technology 40 (1), 297-303 , 2022 2022 Citations: 13
Optimization of 3D Plate Fin Heat Sinks Through Analytical Modelling N Shikalgar, P Chitale, SN Sapali Recent Advances in Thermal Sciences and Engineering: Select Proceedings of … , 2023 2023 Citations: 11
Numerical and Thermal Analysis of Condensers Applied to Domestic Refrigerator SNS Niyaj D Shikalgar International Review of Mechanical Engineering 11 (7), 481-485 , 2017 2017 Citations: 11
Experimental investigation of a capillary tube for 2 TR water chiller with R22 & R407C refrigerant AS Tupe, SN Sapali, N Shikalgar Materials Today: Proceedings 77, 818-822 , 2023 2023 Citations: 10
Mathematical Modeling of a Skin Condenser with Angular Contact for Domestic Refrigerator ND Shikalgar, SN Sapali, AB Shinde Applications of Computation in Mechanical Engineering: Select Proceedings of … , 2022 2022 Citations: 10
Design, Development, and Numerical Analysis of Mist Nozzle and Its Impact on Performance Parameters of an Evaporative Cooler AM Deshmukh, SN Sapali, AB Shinde, ND Shikalgar Applications of Computation in Mechanical Engineering: Select Proceedings of … , 2022 2022 Citations: 9
Predictive Analysis of Air-Cooled Condenser by Considering Fouling Using Machine Learning Algorithm ND Shikalgar, PR Gujari, SN Sapali, VD Chavan Recent Advances in Fluid Dynamics: Select Proceedings of ICAFFTS 2021, 225-234 , 2022 2022 Citations: 5
Safety challenges in high-voltage electric vehicle collisions: risks and design strategies VK Agrawal, LN Patil, ND Shikalgar, YM Patil, V Javanjal, S Gadhave, ... Discover Electronics 2 (1), 53 , 2025 2025 Citations: 2
Experimental evaluation of the effect of leakage in scroll compressor ND Shıkalgar, SN Sapalı Journal of Thermal Engineering 9 (5), 1219-1227 , 2021 2021 Citations: 1
Investigating Splashing Phenomena in Ice Trays Using Multiphase Volume of Fluid Modelling. ND Shikalgar, SR Kandharkar, SS Mundra, RA Patil, NA Rawabawale International Journal of Heat & Technology 43 (6) , 2025 2025
Metal Additive Manufacturing Materials: A State-of-the-Art Review. S Gadhave, S Kandharkar, N Shikalgar, S Nehe, V Mane, K Mahajan, ... Journal of Mines, Metals & Fuels 73 (10) , 2025 2025
Investigating the Structural Integrity of Automotive B-pillars: The Effect of Ply Orientation on Composite Strength. K More, S Kandharkar, R Pawar, H Chavhan, P Honawadajkar, ... Journal of Mines, Metals & Fuels 73 (6) , 2025 2025
Performance assessment of a refrigerator with a hot-wall condenser under O-to-D grooved geometrical conditions N SHIKALGAR, A DESHMUKH, C CHOUDHARI Materials Research Proceedings 49 , 2025 2025
CFD-Based Numerical Investigation of Crossflow Fan Performance N Shikalgar, A Deshmukh, V Zinjurde International Journal of Fluid Mechanics Research 52 (4) , 2025 2025
Unmanned Ground Vehicle: Design and Development Approaches N Shikalgar, Y Patil, A Karale, M Patil, V Thadi, R Bankar 2024 International Conference on Intelligent Systems and Advanced … , 2024 2024
Assessment of Exergy Loss Rate in Marine Boiler to Analyze the Performance of Waste Heat Plant by the Exergy Method JS Pal, SN Sapali, TR Anil, ND Shikalgar Proceedings of the 26thNational and 4th International ISHMT-ASTFE Heat and … , 2021 2021
